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Christy Bergman

Cheng Su

Embedding Inference at Scale for RAG Applications with Ray Data and Milvus

Avnish Narayan

Jun Gong

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Reinforcement learning sessions at Ray Summit: A guided tour

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Biggest takeaways from our RL tutorial: Long-term rewards, offline RL, and more

Amog Kamsetty

Displaying [New York City Yellow Taxi](https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page) ride volumes, with 1 week hourly forecast.  Blue=observed, Orange=predicted, per validation dataset.  Forecast generated using Google’s Temporal Fusion Transformer algorithm implemented by Pytorch forecasting, and parallelized by Ray for faster runtime, either on a laptop or on any cloud.  Image by Author.  

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Time Series Forecasting using an LSTM version of RNN with PyTorch Forecasting and Torch Lightning

New York City Yellow Taxi ride volumes per location 

Scaling Time Series Forecasting on Ray: ARIMA and Prophet on Ray

The Ray Summit 2025 CfP is now open for submissions. The premier AI conference will be held November 3-5 in San Francisco, and the due date for CfPs is June 30th, 2025.  

Ray Summit 2025 CFP Open

Ray Summit 2025: Call for Proposals Closes on June 30th, 2025

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Google Cloud Integrates Anyscale's RayTurbo with GKE

Simplifying AI Development at Scale: Google Cloud Integrates Anyscale's RayTurbo with GKE

At Ray Summit 2024, we brought together AI experts and practitioners to dive into the future of distributed AI and scalable machine learning.

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Ray Summit 2024: Breaking Through the AI Complexity Wall

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Anyscale is the leading AI application platform. With Anyscale, developers can build, run and scale AI applications instantly.

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Featured Posts and News

Ray Summit 2025: Call for Proposals Closes on June 30th, 2025

Simplifying AI Development at Scale: Google Cloud Integrates Anyscale's RayTurbo with GKE

Ray Summit 2024: Breaking Through the AI Complexity Wall

Embedding Inference at Scale for RAG Applications with Ray Data and Milvus

Embedding Inference at Scale for RAG Applications with Ray Data and Milvus

Reinforcement learning sessions at Ray Summit: A guided tour

Biggest takeaways from our RL tutorial: Long-term rewards, offline RL, and more

Time Series Forecasting using an LSTM version of RNN with PyTorch Forecasting and Torch Lightning

Scaling Time Series Forecasting on Ray: ARIMA and Prophet on Ray